A survey of remote sensing-based aboveground biomass estimation methods in forest ecosystems
Remote sensing-based methods of aboveground biomass (AGB) estimation in forest
ecosystems have gained increased attention, and substantial research has been conducted …
ecosystems have gained increased attention, and substantial research has been conducted …
Lidar sheds new light on plant phenomics for plant breeding and management: Recent advances and future prospects
Plant phenomics is a new avenue for linking plant genomics and environmental studies,
thereby improving plant breeding and management. Remote sensing techniques have …
thereby improving plant breeding and management. Remote sensing techniques have …
SemiCDNet: A semisupervised convolutional neural network for change detection in high resolution remote-sensing images
Change detection (CD) is one of the main applications of remote sensing. With the
increasing popularity of deep learning, most recent developments of CD methods have …
increasing popularity of deep learning, most recent developments of CD methods have …
Object-based change detection
Characterizations of land-cover dynamics are among the most important applications of
Earth observation data, providing insights into management, policy and science. Recent …
Earth observation data, providing insights into management, policy and science. Recent …
Canopy laser interception compensation mechanism—UAV LiDAR precise monitoring method for cotton height
Plant height is a crucial phenotypic trait that plays a vital role in predicting cotton growth and
yield, as well as in estimating biomass in cotton plants. The accurate estimation of canopy …
yield, as well as in estimating biomass in cotton plants. The accurate estimation of canopy …
Lidar plots—A new large-area data collection option: Context, concepts, and case study
Forests are an important global resource, playing key roles in both the environment and the
economy. The implementation of quality national monitoring programs is required for the …
economy. The implementation of quality national monitoring programs is required for the …
Effects of LiDAR point density and landscape context on estimates of urban forest biomass
Abstract Light Detection and Ranging (LiDAR) data is being increasingly used as an
effective alternative to conventional optical remote sensing to accurately estimate …
effective alternative to conventional optical remote sensing to accurately estimate …
SemiSiROC: Semisupervised change detection with optical imagery and an unsupervised teacher model
Change detection (CD) is an important yet challenging task in remote sensing. In this article,
we underline that the combination of unsupervised and supervised methods in a …
we underline that the combination of unsupervised and supervised methods in a …
An improved generalized hierarchical estimation framework with geostatistics for map** forest parameters and its uncertainty: a case study of forest canopy height
J Zhao, L Zhao, E Chen, Z Li, K Xu, X Ding - Remote Sensing, 2022 - mdpi.com
Forest canopy height is an essential parameter in estimating forest aboveground biomass
(AGB), growing stock volume (GSV), and carbon storage, and it can provide necessary …
(AGB), growing stock volume (GSV), and carbon storage, and it can provide necessary …
A GEOBIA framework to estimate forest parameters from lidar transects, Quickbird imagery and machine learning: A case study in Quebec, Canada
The GEOgraphic Object-Based Image Analysis (GEOBIA) paradigm continues to prove its
efficacy in remote sensing image analysis by providing tools which emulate human …
efficacy in remote sensing image analysis by providing tools which emulate human …